• Summary
• Downloads
• Explanatory Notes
• Related Information
• Past Releases

4. INVESTMENT IN, AND USE OF, INNOVATIVE TECHNOLOGIES, METHODS AND PROCESSES ACROSS THE STATISTICAL CYCLE

Statistical organisations around the world have long taken advantage of emerging technologies and new techniques to continually improve the efficiency and effectiveness of their statistics. Major developments have included the introduction of computers, and later the internet, into statistical collection and processing, and the development of sample surveys in place of censuses. In recent decades the imperative to stay abreast of emerging technologies has intensified as traditional survey methodologies have become increasingly expensive and resource pressures have forced organisations to search for alternatives. The increasing difficulties faced by organisations in achieving quality response rates from direct collection (i.e. surveying respondents through face-to-face, telephone or self-completed questionnaires) reflects in part an increasingly mobile respondent population that is difficult to capture via traditional mail or landline telephone data capture methods, as well as increasing respondent disengagement in response to survey burden.

At the same time, the opportunities presented by the increased interest in ‘big data’, Web 2.0 and 3.0, remote sensing and sensor technologies and other technological innovations offer the potential to be ‘game changers’ for statistical production in the 21st century. Smart technologies embedded in production systems and along supply chains provide the potential to collect data automatically at source, offering alternative data sources to surveys that would reduce respondent burden and potentially lead to improved data quality, particularly timeliness. Remote sensing has been in use for a number of years in some countries, including the United States, for collection of agricultural data and is being explored in a range of other countries as a means of improving estimation of agricultural production and yields⁵⁹. As well as potentially providing data in a more timely and cost-effective way, use of these sources in place of direct collection has the potential to reduce respondent burden.

For statistical collections that require some form of direct collection, the use of e-forms and smartphone apps offer increased convenience and speed for survey respondents, thereby increasing engagement. Web dissemination modes such as social media provide new avenues for statistical producers to rapidly disseminate statistical products to a wide audience quickly, and to find and source new and existing data sources.

In addition to new technologies, new and improved statistical methods and techniques also create potential to improve the cost-effectiveness, efficiency and relevance of statistical products. Increasingly, statistical organisations are integrating data from various sources, for example through the use of frameworks such as accounting frameworks⁶⁰ or through use of a common presentation format, to assist users wanting to understand complex issues such as those involving social, economic and environmental phenomena. New and improved statistical techniques, including statistical data integration⁶¹ and modelling offer new ways of deriving value from existing and new data sources. Improved confidentiality techniques also offer the potential for more data to be released for public consumption while protecting the privacy of individual businesses.

FOOTNOTES

⁵⁹ See for example the FAO-hosted Expert Group Meeting on Crop Monitoring for Improved Food Security held in February 2014.
⁶⁰ The System of National Accounts and related System of Environmental-Economic Accounts are two examples of internationally-accepted statistical frameworks which provide the capacity to integrate a range of data, expressed in both monetary and physical terms, in a systematic way. More information about the use of these frameworks in Australia is outlined in: ABS 2014, Australian Environmental-Economic Accounts, 2014 (cat. no. 4655.0) and ABS 2013, Australian System of National Accounts: Concepts, Sources and Methods (cat. no. 5216.0).
⁶¹ Statistical data integration involves combining information from different administrative and/or survey sources to provide new datasets for statistical and research purposes. More information about statistical data integration involving Australian Commonwealth Government data can be found on the NSS website.